Central tendency of Yt (Paper)

*The author of this computation has been verified*

R Software Module: /rwasp_centraltendency.wasp (opens new window with default values)

Title produced by software: Central Tendency

Date of computation: Sun, 28 Nov 2010 10:06:42 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Nov/28/t12909387054p5enopcyneuz79.htm/, Retrieved Sun, 28 Nov 2010 11:05:07 +0100

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Nov/28/t12909387054p5enopcyneuz79.htm/}, year = {2010}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2010}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

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9.769 9.321 9.939 9.336 10.195 9.464 10.010 10.213 9.563 9.890 9.305 9.391 9.928 8.686 9.843 9.627 10.074 9.503 10.119 10.000 9.313 9.866 9.172 9.241 9.659 8.904 9.755 9.080 9.435 8.971 10.063 9.793 9.454 9.759 8.820 9.403 9.676 8.642 9.402 9.610 9.294 9.448 10.319 9.548 9.801 9.596 8.923 9.746 9.829 9.125 9.782 9.441 9.162 9.915 10.444 10.209 9.985 9.842 9.429 10.132 9.849 9.172 10.313 9.819 9.955 10.048 10.082 10.541 10.208 10.233 9.439 9.963 10.158 9.225 10.474 9.757 10.490 10.281 10.444 10.640 10.695 10.786 9.832 9.747 10.411 9.511 10.402 9.701 10.540 10.112 10.915 11.183 10.384 10.834 9.886 10.216

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 9.81677083333333 0.0523438959040473 187.543755843636 Geometric Mean 9.80350905583585 Harmonic Mean 9.79023794622693 Quadratic Mean 9.83001925332974 Winsorized Mean ( 1 / 32 ) 9.8144375 0.0515391347911655 190.426896760446 Winsorized Mean ( 2 / 32 ) 9.81554166666667 0.0505591409748139 194.139802959791 Winsorized Mean ( 3 / 32 ) 9.81666666666667 0.0497203554159668 197.437580333833 Winsorized Mean ( 4 / 32 ) 9.81366666666667 0.0488182510689076 201.024544136465 Winsorized Mean ( 5 / 32 ) 9.81330208333334 0.0478133251443342 205.241991719043 Winsorized Mean ( 6 / 32 ) 9.81392708333333 0.045517933724242 215.605724609301 Winsorized Mean ( 7 / 32 ) 9.81713541666667 0.0449612494455915 218.346588178040 Winsorized Mean ( 8 / 32 ) 9.81605208333333 0.0437785129387666 224.220774631225 Winsorized Mean ( 9 / 32 ) 9.81548958333333 0.0433902603338615 226.214120583955 Winsorized Mean ( 10 / 32 ) 9.81236458333333 0.0428984345188125 228.734794017490 Winsorized Mean ( 11 / 32 ) 9.8184375 0.0419690879677709 233.944504763597 Winsorized Mean ( 12 / 32 ) 9.8163125 0.041034309330302 239.222071973588 Winsorized Mean ( 13 / 32 ) 9.82227083333333 0.0398167581288008 246.686854855432 Winsorized Mean ( 14 / 32 ) 9.82125 0.0391939789056450 250.580580850021 Winsorized Mean ( 15 / 32 ) 9.81234375 0.0375296807339514 261.455561521023 Winsorized Mean ( 16 / 32 ) 9.81267708333333 0.0372017216128916 263.769434797687 Winsorized Mean ( 17 / 32 ) 9.80966666666667 0.0360418940769623 272.174005220689 Winsorized Mean ( 18 / 32 ) 9.81097916666667 0.0334271890699098 293.502966885667 Winsorized Mean ( 19 / 32 ) 9.80979166666667 0.0326966986794105 300.023918709690 Winsorized Mean ( 20 / 32 ) 9.809375 0.0325877400326963 301.014276846383 Winsorized Mean ( 21 / 32 ) 9.8141875 0.0317366849843184 309.237953013976 Winsorized Mean ( 22 / 32 ) 9.81533333333333 0.0315315341554900 311.286259809987 Winsorized Mean ( 23 / 32 ) 9.81317708333333 0.0310037844138523 316.515459930397 Winsorized Mean ( 24 / 32 ) 9.80442708333333 0.0297615219645651 329.432987163988 Winsorized Mean ( 25 / 32 ) 9.79947916666667 0.0286902582157065 341.561204956389 Winsorized Mean ( 26 / 32 ) 9.79758333333333 0.0280536245065270 349.244830415899 Winsorized Mean ( 27 / 32 ) 9.79842708333333 0.0274549421332851 356.891194152407 Winsorized Mean ( 28 / 32 ) 9.80105208333333 0.0249656622507992 392.581297658931 Winsorized Mean ( 29 / 32 ) 9.80105208333333 0.0243769032985734 402.063049735563 Winsorized Mean ( 30 / 32 ) 9.80917708333333 0.0225406795749358 435.176634791468 Winsorized Mean ( 31 / 32 ) 9.80917708333333 0.0213797893720837 458.806067385374 Winsorized Mean ( 32 / 32 ) 9.80751041666667 0.0185811283885332 527.821034954964 Trimmed Mean ( 1 / 32 ) 9.81473404255319 0.0498690556589524 196.810104239286 Trimmed Mean ( 2 / 32 ) 9.81504347826087 0.0479588679302319 204.655445423343 Trimmed Mean ( 3 / 32 ) 9.81477777777778 0.0463763758195027 211.633134421219 Trimmed Mean ( 4 / 32 ) 9.8140909090909 0.0449294455498837 218.433385700134 Trimmed Mean ( 5 / 32 ) 9.81420930232558 0.0435823641721536 225.187630105579 Trimmed Mean ( 6 / 32 ) 9.81441666666667 0.0423286638081786 231.862189440772 Trimmed Mean ( 7 / 32 ) 9.81451219512195 0.0414734462774848 236.645687205649 Trimmed Mean ( 8 / 32 ) 9.8140625 0.0406100136671667 241.666072324785 Trimmed Mean ( 9 / 32 ) 9.8137564102564 0.0398563236567346 246.228339943696 Trimmed Mean ( 10 / 32 ) 9.81351315789474 0.0390521760447731 251.292351715398 Trimmed Mean ( 11 / 32 ) 9.81366216216216 0.0382025296997927 256.885139263838 Trimmed Mean ( 12 / 32 ) 9.81308333333333 0.037372593950116 262.574317063236 Trimmed Mean ( 13 / 32 ) 9.81271428571429 0.0365578819695881 268.415831471783 Trimmed Mean ( 14 / 32 ) 9.81167647058824 0.0357989118559306 274.077505765383 Trimmed Mean ( 15 / 32 ) 9.81068181818182 0.0349973569371056 280.326363954077 Trimmed Mean ( 16 / 32 ) 9.810515625 0.0343172494124436 285.877096590458 Trimmed Mean ( 17 / 32 ) 9.8103064516129 0.0335469755860772 292.434900023727 Trimmed Mean ( 18 / 32 ) 9.81036666666667 0.0328054612260269 299.046753193746 Trimmed Mean ( 19 / 32 ) 9.81031034482759 0.0323287260133808 303.454900782886 Trimmed Mean ( 20 / 32 ) 9.81035714285714 0.0318476122835490 308.040585759225 Trimmed Mean ( 21 / 32 ) 9.81044444444444 0.0312554192831883 313.879790111192 Trimmed Mean ( 22 / 32 ) 9.81011538461538 0.0306511738749781 320.056759477776 Trimmed Mean ( 23 / 32 ) 9.80966 0.0299148807417967 327.919074278443 Trimmed Mean ( 24 / 32 ) 9.80935416666667 0.0290712088809672 337.425051941641 Trimmed Mean ( 25 / 32 ) 9.80978260869565 0.0282276616489502 347.523742160927 Trimmed Mean ( 26 / 32 ) 9.81068181818182 0.0273439406757307 358.78814741905 Trimmed Mean ( 27 / 32 ) 9.81183333333333 0.0263132853455354 372.885149250209 Trimmed Mean ( 28 / 32 ) 9.813025 0.0250787091103395 391.289079387035 Trimmed Mean ( 29 / 32 ) 9.8141052631579 0.0240412397424752 408.21959966643 Trimmed Mean ( 30 / 32 ) 9.81530555555556 0.0227681837131194 431.097433121107 Trimmed Mean ( 31 / 32 ) 9.81588235294118 0.0215354354878283 455.80143287509 Trimmed Mean ( 32 / 32 ) 9.81653125 0.0201434865190499 487.330296109187 Median 9.824 Midrange 9.9125 Midmean - Weighted Average at Xnp 9.80179591836735 Midmean - Weighted Average at X(n+1)p 9.80935416666667 Midmean - Empirical Distribution Function 9.80179591836735 Midmean - Empirical Distribution Function - Averaging 9.80935416666667 Midmean - Empirical Distribution Function - Interpolation 9.80935416666667 Midmean - Closest Observation 9.80179591836735 Midmean - True Basic - Statistics Graphics Toolkit 9.80935416666667 Midmean - MS Excel (old versions) 9.80966 Number of observations 96

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/28/t12909387054p5enopcyneuz79/1zutn1290938799.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/28/t12909387054p5enopcyneuz79/1zutn1290938799.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/28/t12909387054p5enopcyneuz79/2zutn1290938799.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/28/t12909387054p5enopcyneuz79/2zutn1290938799.ps (open in new window)

Parameters (Session):

Parameters (R input):

R code (references can be found in the software module):

geomean <- function(x) { return(exp(mean(log(x)))) } harmean <- function(x) { return(1/mean(1/x)) } quamean <- function(x) { return(sqrt(mean(x*x))) } winmean <- function(x) { x <-sort(x[!is.na(x)]) n<-length(x) denom <- 3 nodenom <- n/denom if (nodenom>40) denom <- n/40 sqrtn = sqrt(n) roundnodenom = floor(nodenom) win <- array(NA,dim=c(roundnodenom,2)) for (j in 1:roundnodenom) { win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn } return(win) } trimean <- function(x) { x <-sort(x[!is.na(x)]) n<-length(x) denom <- 3 nodenom <- n/denom if (nodenom>40) denom <- n/40 sqrtn = sqrt(n) roundnodenom = floor(nodenom) tri <- array(NA,dim=c(roundnodenom,2)) for (j in 1:roundnodenom) { tri[j,1] <- mean(x,trim=j/n) tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2) } return(tri) } midrange <- function(x) { return((max(x)+min(x))/2) } q1 <- function(data,n,p,i,f) { np <- n*p; i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q2 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q3 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- data[i+1] } } q4 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- (data[i]+data[i+1])/2 } else { qvalue <- data[i+1] } } q5 <- function(data,n,p,i,f) { np <- (n-1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i+1] } else { qvalue <- data[i+1] + f*(data[i+2]-data[i+1]) } } q6 <- function(data,n,p,i,f) { np <- n*p+0.5 i <<- floor(np) f <<- np - i qvalue <- data[i] } q7 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- f*data[i] + (1-f)*data[i+1] } } q8 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { if (f == 0.5) { qvalue <- (data[i]+data[i+1])/2 } else { if (f < 0.5) { qvalue <- data[i] } else { qvalue <- data[i+1] } } } } midmean <- function(x,def) { x <-sort(x[!is.na(x)]) n<-length(x) if (def==1) { qvalue1 <- q1(x,n,0.25,i,f) qvalue3 <- q1(x,n,0.75,i,f) } if (def==2) { qvalue1 <- q2(x,n,0.25,i,f) qvalue3 <- q2(x,n,0.75,i,f) } if (def==3) { qvalue1 <- q3(x,n,0.25,i,f) qvalue3 <- q3(x,n,0.75,i,f) } if (def==4) { qvalue1 <- q4(x,n,0.25,i,f) qvalue3 <- q4(x,n,0.75,i,f) } if (def==5) { qvalue1 <- q5(x,n,0.25,i,f) qvalue3 <- q5(x,n,0.75,i,f) } if (def==6) { qvalue1 <- q6(x,n,0.25,i,f) qvalue3 <- q6(x,n,0.75,i,f) } if (def==7) { qvalue1 <- q7(x,n,0.25,i,f) qvalue3 <- q7(x,n,0.75,i,f) } if (def==8) { qvalue1 <- q8(x,n,0.25,i,f) qvalue3 <- q8(x,n,0.75,i,f) } midm <- 0 myn <- 0 roundno4 <- round(n/4) round3no4 <- round(3*n/4) for (i in 1:n) { if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){ midm = midm + x[i] myn = myn + 1 } } midm = midm / myn return(midm) } (arm <- mean(x)) sqrtn <- sqrt(length(x)) (armse <- sd(x) / sqrtn) (armose <- arm / armse) (geo <- geomean(x)) (har <- harmean(x)) (qua <- quamean(x)) (win <- winmean(x)) (tri <- trimean(x)) (midr <- midrange(x)) midm <- array(NA,dim=8) for (j in 1:8) midm[j] <- midmean(x,j) midm bitmap(file='test1.png') lb <- win[,1] - 2*win[,2] ub <- win[,1] + 2*win[,2] if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax)) lines(ub,lty=3) lines(lb,lty=3) grid() dev.off() bitmap(file='test2.png') lb <- tri[,1] - 2*tri[,2] ub <- tri[,1] + 2*tri[,2] if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax)) lines(ub,lty=3) lines(lb,lty=3) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Measure',header=TRUE) a<-table.element(a,'Value',header=TRUE) a<-table.element(a,'S.E.',header=TRUE) a<-table.element(a,'Value/S.E.',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE) a<-table.element(a,arm) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean')) a<-table.element(a,armose) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE) a<-table.element(a,geo) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE) a<-table.element(a,har) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE) a<-table.element(a,qua) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) for (j in 1:length(win[,1])) { a<-table.row.start(a) mylabel <- paste('Winsorized Mean (',j) mylabel <- paste(mylabel,'/') mylabel <- paste(mylabel,length(win[,1])) mylabel <- paste(mylabel,')') a<-table.element(a,hyperlink('http://www.xycoon.com/winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE) a<-table.element(a,win[j,1]) a<-table.element(a,win[j,2]) a<-table.element(a,win[j,1]/win[j,2]) a<-table.row.end(a) } for (j in 1:length(tri[,1])) { a<-table.row.start(a) mylabel <- paste('Trimmed Mean (',j) mylabel <- paste(mylabel,'/') mylabel <- paste(mylabel,length(tri[,1])) mylabel <- paste(mylabel,')') a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE) a<-table.element(a,tri[j,1]) a<-table.element(a,tri[j,2]) a<-table.element(a,tri[j,1]/tri[j,2]) a<-table.row.end(a) } a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE) a<-table.element(a,median(x)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE) a<-table.element(a,midr) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_1.htm','Weighted Average at Xnp',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[1]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[2]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_3.htm','Empirical Distribution Function',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[3]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[4]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[5]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_6.htm','Closest Observation',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[6]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[7]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_8.htm','MS Excel (old versions)',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[8]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Number of observations',header=TRUE) a<-table.element(a,length(x)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

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